Competing in a supply chain via full-refund and no-refund customer returns policies

Chen, Jing; Grewal, Ravneet

doi:10.1016/j.ijpe.2013.07.005

Cited by 74 publications

(31 citation statements)

References 30 publications

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“…It is confirmed that the profit of manufacturer is the double of the retailer's when a price-versus-demand relationship exists of a two-echelon supply chain in [4]. Other related researches in recent years are in [5][6][7][8][9].…”

Section: Introductionmentioning

confidence: 73%

Price Decision Models of a Manufacturer-retailer Supply Chain Based on Game Theory

Zhao¹,

Chen²

2015

Proceedings of the AASRI International Conference on Industrial Electronics and Applications (2015)

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This paper focuses on the pricing decision problem of a two-echelon supply chain consisting of one manufacturer and two retailers in which the manufacturer acts as a leader. The price decision models are developed by considering the sensitivity of the retail quantity to the wholesale price of the manufacturer and the sale prices of the retailers. The optimal decisions are discussed and analyzed under retailers' different game behavior: Cournot, Collusion and Stackelberg. The research indicates that the duopolistic retailers could charge the highest price to customers and gain the greatest profit in the Collusion solution and it is reverse in the Cournot solution, but the leader's profit may be fewer than the follower in the Stackelberg situation Keywords-manufacturer-retailer supply chain; pricing; game behaviour.

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Section: Introductionmentioning

confidence: 73%

Price Decision Models of a Manufacturer-retailer Supply Chain Based on Game Theory

Zhao¹,

Chen²

2015

Proceedings of the AASRI International Conference on Industrial Electronics and Applications (2015)

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“…Low-quality retailer increases profits while high-quality retailer decreases profits, compared to the case where neither retailer offers an MBG. Chen and Grewal (2013) Nash and Stackelberg Two retailers, one established and offering an MBG, the other a new entrant and considering whether to offer an MBG.…”

Section: Shulman Et Al (2011)mentioning

confidence: 99%

Taking stock of consumer returns: A review and classification of the literature

Abdulla

Ketzenberg

Abbey

2019

J of Ops Management

111

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Coincident with the rapid growth of consumer returns and their corresponding importance in the retail marketplace, academic interest in the area of consumer return policy design has significantly increased. In fact, the growth in academic publications has been tremendous, with almost half of the published works appearing within the past 6 years. The influx of new and evolving research spans across multiple disciplines and various methodologies. To provide clarity for the continued evolution of the field, we provide a comprehensive review and classification of the literature predicated on a holistic conceptual framework. The scope of the review includes all peer reviewed journal articles published prior to the end of 2018, along with any working papers cited therefrom, that specifically address (a) managerial decision‐making related to return policies or (b) consumer behavior in response to such decision‐making. Examining the state of the literature and practice on return policy design through the lens of a unified conceptual framework—a framework that spans both analytical and empirical research—reveals numerous managerial and theoretical opportunities for future research.

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“…A large body of work on customer returns has examined a refund policy that is exogenously determined as a full refund or a Money Back Guarantee (MBG) (Chang and Yeh 2013;Chen and Bell 2013;Choi et al 2013;Akcay, Boyaci and Zhang 2013;Wang, Tung and Lee 2010;You, Ikuta and Hsieh 2010;Vlachos and Dekker 2003). Other papers have compared a system's performance with no refund policy to a system's performance with a full refund policy (Chen and Grewal 2013;Choi et al 2013;Chen and Bell 2012;Chen and Zhang 2011).…”

Section: Related Workmentioning

confidence: 99%

“…The probability that a product purchased from an online store is cross-returned to a physical store is 0 ≤ ≤ 1 (Figure 1). The assumption of ratios for returns has been implemented in literature before, such as in works by Chen and Grewal (2013), Mostard and Teunter (2006), Mostard, Koster and Teunter (2005), Vlachos and Dekker (2003), and many more. as new"; thus, it can be resold at least one more time during a selling season.…”

Section: Problem Statementmentioning

confidence: 99%